An application of stakeholder theory to advance community participation in tourism planning: the case for engaging immigrants as fringe stakeholders
Bibliographic record
Abstract
Anahita Khazaeia*, Statia Elliota & Marion Joppeaa School of Hospitality, Food and Tourism Management, University of Guelph, Guelph, CanadaAnahita Khazaei is a PhD candidate and instructor in the School of Hospitality, Food and Tourism Management, University of Guelph, Canada. Her research interests include community engagement, tourism planning and sustainability. Anahita has years of experience in strategic planning acquired while she was a management consultant in her native country of Iran.Dr Statia Elliot is an associate professor, and director of the School of Hospitality, Food and Tourism Management, University of Guelph. She has extensive experience working with Canadian destination marketing organizations, and specializes in research of place image and branding, tourism destination planning and performance. She teaches strategic marketing and tourism, and is chair of the Canadian Chapter of the Travel and Tourism Research Association.Dr Marion Joppe is a professor in the School of Hospitality, Food and Tourism Management, University of Guelph. She obtained her doctorate from the University of Aix-Marseille III, France, in law and economics of tourism in 1983, and specializes in destination planning, development and marketing, and the experiences upon which destinations build. She has extensive private and public sector experience, having worked for financial institutions, tour operators, consulting groups and government, and has published in both North America and Europe.* Corresponding author. Email: akhazaei@uoguelph.caCommunity participation has long been viewed as an important tenet of tourism planning, and there is general consensus among researchers that engaging all stakeholder groups contributes to tourism sustainability. However, there are gaps in the literature, and challenges in practice, that call for further research. Among these are the dynamics of heterogeneous community groups and that not all community subgroups have equal opportunity to participate in tourism planning. This paper attempts to advance community participation by drawing on progressive approaches to stakeholder theory in the management field and by exploring, for the first time, the engagement of immigrants in tourism planning as fringe stakeholders, representative of present and future community dynamics. Bringing first generation immigrants as an important but less studied segment within the broader host community into focus moves tourism planning toward a more inclusive approach to community engagement, reflecting increased diversity and change in host communities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.025 | 0.027 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.003 | 0.018 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".